Variable precision rough set model
Journal of Computer and System Sciences
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Theoretical foundations of order-based genetic algorithms
Fundamenta Informaticae - Special issue: to the memory of Prof. Helena Rasiowa
Data mining methods for knowledge discovery
Data mining methods for knowledge discovery
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Taming Large Rule Models in Rough Set Approaches
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
Covering with Reducts - A Fast Algorithm for Rule Generation
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Application of Normalized Decision Measures to the New Case Classification
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
On Construction of Partial Reducts and Irreducible Partial Decision Rules
Fundamenta Informaticae - New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak
Greedy Algorithm for Construction of Partial Association Rules
Fundamenta Informaticae
Greedy Algorithms withWeights for Construction of Partial Association Rules
Fundamenta Informaticae
Greedy Algorithm for Attribute Reduction
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
On Construction of Partial Reducts and Irreducible Partial Decision Rules
Fundamenta Informaticae - New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
Dynamic Programming Approach for Partial Decision Rule Optimization
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Dynamic programming approach to optimization of approximate decision rules
Information Sciences: an International Journal
A Novel Emotion Recognition Method Based on Ensemble Learning and Rough Set Theory
International Journal of Cognitive Informatics and Natural Intelligence
Optimization of β-decision rules relative to number of misclassifications
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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The problem of improving rough set based expert systems by modifying a notion of reduct is discussed. The notion of approximate reduct is introduced, as well as some proposals of quality measure for such a reduct. The complete classifying system based on approximate reducts is presented and discussed. It is proved that the problem of finding optimal set of classifying agents based on approximate reducts is NP-hard; the genetic algorithm is applied to find the suboptimal set. Experimental results show that the classifying system is effective and relatively fast.